gstack-openclaw-retro

Analyze Git history to generate weekly engineering retrospectives with per-author metrics.

Updated May 6, 2026
One-click install
npx skills add https://github.com/stayconnectquick/gstack --skill gstack-openclaw-retro-stayconnectquick
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gstack-openclaw-retro
Source: https://github.com/stayconnectquick/gstack/tree/main/openclaw/skills/gstack-openclaw-retro
Command: npx skills add https://github.com/stayconnectquick/gstack --skill gstack-openclaw-retro-stayconnectquick

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Provides a structured, team-aware weekly engineering retrospective by analyzing commit history, work patterns, and code quality metrics, with persistent history and growth-oriented feedback.

Core Features & Use Cases

  • Team-wide metrics: per-author commits, LOC, praise, and growth opportunities.
  • Time and session analysis: identify coding windows, peak hours, and session lengths.
  • Ship & focus insights: highlight the top-LOC PRs, hotspots, and focus scores.
  • Narrative for sharing: generate Telegram-ready summaries and a memory-storable JSON snapshot.

Quick Start

Ask for a weekly retro to cover the last 7 days and it will generate the full report.

Frequently Asked Questions about gstack-openclaw-retro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate a weekly engineering retro from Git history?▼

Generate a weekly engineering retro by applying the Skill to 7-14 days of team Git history to produce per-author LOC, commit metrics, session patterns, and a Telegram-ready narrative.

What metrics are included in a team-wide code retrospective?▼

A team-wide code retrospective includes per-author commits, LOC, PR sizes, hotspot files, focus scores, time distribution, and a concise ship and wins summary.

Can I analyze coding session patterns and peak hours from commit data?▼

Yes, you can analyze coding session patterns by evaluating Git history to identify coding windows, peak hours, session lengths, and time distribution.

How do I share engineering metrics as a Telegram-ready summary?▼

Share engineering metrics by generating a narrative summary from Git history formatted for Telegram, alongside a memory-storable JSON snapshot of the retro data.

Does this weekly retro analysis work for individual developers or only teams?▼

The weekly retro analysis is team-aware and designed for team-wide application over a 7-14 day window, producing per-author metrics, focus scores, and growth-oriented feedback.